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 2012 Jan 1;41(1):89-98.

A Simple Distribution-Free Algorithm for Generating Simulated High-Dimensional Correlated Data with an Autoregressive Structure.


Department of Community Health Outcomes and Systems, University of Alabama at Birmingham, Birmingham, Alabama, USA.


A distribution-free method to generate high-dimensional sequences of dependent variables with an autoregressive structure is presented. The quantile or fractile correlation (i.e., the moment correlation of the quantiles) is used as measure of dependence among a set of contiguous variables. The proposed algorithm breaks the sequence in small parts and avoids having to define one large correlation matrix for the entire high-dimensional sequence of variables. Simulations based on proteomics data are presented. Results suggest that negligible or no loss of fractile correlation occurs by splitting the generation of a sequence into small parts.

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